Evidence map›Paper›PMID 35754280›Full record

ReviewJournal of Alzheimer's disease : JAD2022

A Novel Explainability Approach for Technology-Driven Translational Research on Brain Aging.

Adam Turnbull, Robert M Kaplan, Ehsan Adeli, Feng V Lin

Abstract readReview
In one paragraph

Review in Journal of Alzheimer's disease : JAD, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Adam TurnbullDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Robert M KaplanClinical Excellence Research Center (CERC), Stanford University, Stanford, CA, USA.
Ehsan AdeliDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
Feng V LinDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.

Funding

Targeting Autonomic Flexibility to Enhance Cognitive Training Outcomes in Older Adults with Mild Cognitive ImpairmentR01NR015452 · NINR · UNIVERSITY OF ROCHESTER · PI HEFFNER, KATHI L, LIN, FENG VANKEE · 2015 to 2024
$4.4M
Develop an ANS-based Personalized Cognitive Training for Mild Cognitive ImpairmentR33AG073356 · NIA · STANFORD UNIVERSITY · PI LIN, FENG VANKEE, TAPPARELLO, CRISTIANO · 2023 to 2025
$2.2M
Develop an ANS-based Personalized Cognitive Training for Mild Cognitive ImpairmentR21AG073356 · NIA · STANFORD UNIVERSITY · PI LIN, FENG VANKEE, TAPPARELLO, CRISTIANO · 2021 to 2023
$476k
NIA NIH HHS R21 AG073356NIA NIH HHS R33 AG073356NINR NIH HHS R01 NR015452
6 · The paper itself

Abstract

Brain aging leads to difficulties in functional independence. Mitigating these difficulties can benefit from technology that predicts, monitors, and modifies brain aging. Translational research prioritizes solutions that can be causally linked to specific pathophysiologies at the same time as demonstrating improvements in impactful real-world outcome measures. This poses a challenge for brain aging technology that needs to address the tension between mechanism-driven precision and clinical relevance. In the current opinion, by synthesizing emerging mechanistic, translational, and clinical research-related frameworks, and our own development of technology-driven brain aging research, we suggest incorporating the appreciation of four desiderata (causality, informativeness, transferability, and fairness) of explainability into early-stage research that designs and tests brain aging technology. We apply a series of work on electrocardiography-based "peripheral" neuroplasticity markers from our work as an illustration of our proposed approach. We believe this novel approach will promote the development and adoption of brain aging technology that links and addresses brain pathophysiology and functional independence in the field of translational research.

Indexed as

Brain DiseasesTranslational Research, BiomedicalAgingBrainHumansTechnologyArtificial intelligencebrain agingexplainabilitytechnologytranslational research

Identifiers

PMID35754280
PMCPMC9399001

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.